Microarray Data Analysis Methods and Applications

In this new volume, renowned authors contribute fascinating, cutting-edge insights into microarray data analysis. Included in this innovative book includes are in-depth looks intopresentations of genomic signal processing, artificial neural network use for microarray data analysis, signal processing and design of microarray time series experiments, application of regression methods, gene expression sprofiles and prognostic markers for primary breast cancer, and factors affecting the cross-correlation of gene expression profiles. Also detailed are use of tiling arrays for large genomes analysis using tiling arrays, acomparative genomic hybridization data on cDNA microarrays, integrated high-resolution genome-wide analysis of gene dosage and gene expression in human brain tumors, gene and MeSH ontology, and predicting survival prediction in follicular lymphoma using tissue microarrays. The protocols follow the successful Methods in Molecular BiologyTM series format, offering step-by-step instructions, an introduction outlining the principles behind the technique, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding pitfalls.